The flexible specification of HCL-based color palettes in colorspace allows to closely approximate color palettes from various other packages:
See the discussion of HCL-based palettes for more details. In the following specplot() is used to compare the HCL spectrum of the original palettes (top swatch, solid lines) and their HCL-based approximations (bottom swatch, dashed lines).
demo("brewer", package = "colorspace")
demo("carto", package = "colorspace")
demo("viridis", package = "colorspace")
demo("scico", package = "colorspace")
CARTO. 2018. “CARTOColors – Data-Driven Color Schemes.” https://carto.com/carto-colors/.
Crameri, Fabio. 2018. “Geodynamic Diagnostics, Scientific Visualisation and Staglab 3.0.” Geoscientific Model Development 11 (6): 2541–62. doi:10.5194/gmd-11-2541-2018.
Garnier, Simon. 2018. Viridis: Default Color Maps from Matplotlib. https://CRAN.R-project.org/package=viridis.
Harrower, Mark A., and Cynthia A. Brewer. 2003. “ColorBrewer.org: An Online Tool for Selecting Color Schemes for Maps.” The Cartographic Journal 40: 27–37. http://ColorBrewer.org/.
Neuwirth, Erich. 2014. RColorBrewer: ColorBrewer Palettes. https://CRAN.R-project.org/package=RColorBrewer.
Nowosad, Jakub. 2018. Rcartocolor: “CARTOColors” Palettes. https://CRAN.R-project.org/package=rcartocolor.
Pedersen, Thomas Lin, and Fabio Crameri. 2018. Scico: Colour Palettes Based on the Scientific Colour-Maps. https://CRAN.R-project.org/package=scico.
Smith, Nathaniel, and Stéfan Van der Walt. 2015. “A Better Default Colormap for Matplotlib.” In. Austin. https://www.youtube.com/watch?v=xAoljeRJ3lU.